Method and System for Providing Analyte Monitoring

ABSTRACT

Methods and apparatuses for determining an analyte value are disclosed.

RELATED APPLICATIONS

The present application is a continuation of U.S. patent application no.12/506,227 filed Jul. 20, 2009, which is a continuation of U.S. patentapplication Ser. No. 11/552,935 filed Oct. 25, 2006, now U.S. Pat. No.7,630,748, entitled “Method and System for Providing AnalyteMonitoring,” the disclosures of each of which are incorporated herein byreference for all purposes.

BACKGROUND

Analyte, e.g., glucose monitoring systems including continuous anddiscrete monitoring systems generally include a small, lightweightbattery powered and microprocessor controlled system which is configuredto detect signals proportional to the corresponding measured glucoselevels using an electrometer, and RF signals to transmit the collecteddata. One aspect of certain analyte monitoring systems include atranscutaneous or subcutaneous analyte sensor configuration which is,for example, partially mounted on the skin of a subject whose analytelevel is to be monitored. The sensor cell may use a two orthree-electrode (work, reference and counter electrodes) configurationdriven by a controlled potential (potentiostat) analog circuit connectedthrough a contact system.

The analyte sensor may be configured so that a portion thereof is placedunder the skin of the patient so as to detect the analyte levels of thepatient, and another segment of the analyte sensor that is incommunication with the transmitter unit. The transmitter unit isconfigured to transmit the analyte levels detected by the sensor over awireless communication link such as an RF (radio frequency)communication link to a receiver/monitor unit. The receiver/monitor unitperforms data analysis, among others on the received analyte levels togenerate information pertaining to the monitored analyte levels.

To obtain accurate data from the analyte sensor, calibration usingcapillary blood glucose measurements is necessary. Typically, bloodglucose measurements are obtained using, for example, a blood glucosemeter, and the measured blood glucose values are used to calibrate thesensors. Due to a lag factor between the monitored sensor data and themeasured blood glucose values, an error, or signal noise such as signaldropouts, is typically introduced in calibration using the monitoreddata as well as in computing the displayed glucose value. Whilecorrecting for the lag factors can minimize the error due to lag in thepresence of noise, in the presence of signal dropouts, such errorcompensation may reduce accuracy of the monitored sensor data.

In view of the foregoing, it would be desirable to have a method andsystem for providing noise filtering and signal dropout detection and/orcompensation in data monitoring systems.

SUMMARY OF THE INVENTION

In one embodiment, a method for minimizing the effect of noise andsignal dropouts in a glucose sensor including monitoring a data stream,generating a noise-filtered signal associated with the data stream,determining a presence of a signal dropout based on the noise filteredsignal, and estimating a noise filtered dropout compensated signal basedon the noise filtered signal and the determination of the presence ofthe signal dropout are disclosed.

These and other objects, features and advantages of the presentinvention will become more fully apparent from the following detaileddescription of the embodiments, the appended claims and the accompanyingdrawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a block diagram of a data monitoring and managementsystem for practicing one or more embodiments of the present invention;

FIG. 2 is a block diagram of the transmitter unit of the data monitoringand management system shown in FIG. 1 in accordance with one embodimentof the present invention;

FIG. 3 is a block diagram of the receiver/monitor unit of the datamonitoring and management system shown in FIG. 1 in accordance with oneembodiment of the present invention;

FIG. 4 is a functional diagram of the overall signal processing fornoise filtering and signal dropout compensation in accordance with oneembodiment of the present invention;

FIG. 5 is a flowchart illustrating the overall signal processing fornoise filtering and signal dropout compensation in accordance with oneembodiment of the present invention;

FIG. 6 is a flowchart illustrating the process input estimation inaccordance with one embodiment of the present invention;

FIG. 7 is a flowchart illustrating the noise filtered estimation;

FIG. 8 is a flowchart illustrating signal dropout detection inaccordance with one embodiment of the present invention;

FIG. 9 is a flowchart illustrating an overall signal dropoutcompensation in accordance with one embodiment of the present invention;and

FIG. 10 is flowchart illustrating a detailed signal dropout compensationdetermination of FIG. 9 in accordance with one embodiment of the presentinvention.

DETAILED DESCRIPTION

As described in further detail below, in accordance with the variousembodiments of the present invention, there is provided a method andsystem for providing noise filtered and/or signal dropout mitigatedprocesses for signals in analyte monitoring systems. In particular,within the scope of the present invention, there are provided method andsystem for noise filtering, signal dropout detection, and signal dropoutcompensation to improve the accuracy of lag compensation.

FIG. 1 illustrates a data monitoring and management system such as, forexample, analyte (e.g., glucose) monitoring system 100 in accordancewith one embodiment of the present invention. The subject invention isfurther described primarily with respect to a glucose monitoring systemfor convenience and such description is in no way intended to limit thescope of the invention. It is to be understood that the analytemonitoring system may be configured to monitor a variety of analytes,e.g., lactate, and the like.

Analytes that may be monitored include, for example, acetyl choline,amylase, bilirubin, cholesterol, chorionic gonadotropin, creatine kinase(e.g., CK-MB), creatine, DNA, fructosamine, glucose, glutamine, growthhormones, hormones, ketones, lactate, peroxide, prostate-specificantigen, prothrombin, RNA, thyroid stimulating hormone, and troponin.The concentration of drugs, such as, for example, antibiotics (e.g.,gentamicin, vancomycin, and the like), digitoxin, digoxin, drugs ofabuse, theophylline, and warfarin, may also be monitored.

The analyte monitoring system 100 includes a sensor 101, a transmitterunit 102 coupled to the sensor 101, and a primary receiver unit 104which is configured to communicate with the transmitter unit 102 via acommunication link 103. The primary receiver unit 104 may be furtherconfigured to transmit data to a data processing terminal 105 forevaluating the data received by the primary receiver unit 104. Moreover,the data processing terminal in one embodiment may be configured toreceive data directly from the transmitter unit 102 via a communicationlink which may optionally be configured for bi-directionalcommunication.

Also shown in FIG. 1 is a secondary receiver unit 106 which isoperatively coupled to the communication link and configured to receivedata transmitted from the transmitter unit 102. Moreover, as shown inthe Figure, the secondary receiver unit 106 is configured to communicatewith the primary receiver unit 104 as well as the data processingterminal 105. Indeed, the secondary receiver unit 106 may be configuredfor bi-directional wireless communication with each of the primaryreceiver unit 104 and the data processing terminal 105. As discussed infurther detail below, in one embodiment of the present invention, thesecondary receiver unit 106 may be configured to include a limitednumber of functions and features as compared with the primary receiverunit 104. As such, the secondary receiver unit 106 may be configuredsubstantially in a smaller compact housing or embodied in a device suchas a wrist watch, for example. Alternatively, the secondary receiverunit 106 may be configured with the same or substantially similarfunctionality as the primary receiver unit 104, and may be configured tobe used in conjunction with a docking cradle unit for placement bybedside, for night time monitoring, and/or bi-directional communicationdevice.

Only one sensor 101, transmitter unit 102, communication link 103, anddata processing terminal 105 are shown in the embodiment of the analytemonitoring system 100 illustrated in FIG. 1. However, it will beappreciated by one of ordinary skill in the art that the analytemonitoring system 100 may include one or more sensor 101, transmitterunit 102, communication link 103, and data processing terminal 105.Moreover, within the scope of the present invention, the analytemonitoring system 100 may be a continuous monitoring system, orsemi-continuous, or a discrete monitoring system. In a multi-componentenvironment, each device is configured to be uniquely identified by eachof the other devices in the system so that communication conflict isreadily resolved between the various components within the analytemonitoring system 100.

In one embodiment of the present invention, the sensor 101 is physicallypositioned in or on the body of a user whose analyte level is beingmonitored. The sensor 101 may be configured to continuously sample theanalyte level of the user and convert the sampled analyte level into acorresponding data signal for transmission by the transmitter unit 102.In one embodiment, the transmitter unit 102 is mounted on the sensor 101so that both devices are positioned on the user's body. The transmitterunit 102 performs data processing such as filtering and encoding on datasignals, each of which corresponds to a sampled analyte level of theuser, for transmission to the primary receiver unit 104 via thecommunication link 103.

In one embodiment, the analyte monitoring system 100 is configured as aone-way RF communication path from the transmitter unit 102 to theprimary receiver unit 104. In such embodiment, the transmitter unit 102transmits the sampled data signals received from the sensor 101 withoutacknowledgement from the primary receiver unit 104 that the transmittedsampled data signals have been received. For example, the transmitterunit 102 may be configured to transmit the encoded sampled data signalsat a fixed rate (e.g., at one minute intervals) after the completion ofthe initial power on procedure. Likewise, the primary receiver unit 104may be configured to detect such transmitted encoded sampled datasignals at predetermined time intervals. Alternatively, the analytemonitoring system 100 may be configured with a bi-directional RF (orotherwise) communication between the transmitter unit 102 and theprimary receiver unit 104.

Additionally, in one aspect, the primary receiver unit 104 may includetwo sections. The first section is an analog interface section that isconfigured to communicate with the transmitter unit 102 via thecommunication link 103. In one embodiment, the analog interface sectionmay include an RF receiver and an antenna for receiving and amplifyingthe data signals from the transmitter unit 102, which are thereafter,demodulated with a local oscillator and filtered through a band-passfilter. The second section of the primary receiver unit 104 is a dataprocessing section which is configured to process the data signalsreceived from the transmitter unit 102 such as by performing datadecoding, error detection and correction, data clock generation, anddata bit recovery.

In operation, upon completing the power-on procedure, the primaryreceiver unit 104 is configured to detect the presence of thetransmitter unit 102 within its range based on, for example, thestrength of the detected data signals received from the transmitter unit102 or a predetermined transmitter identification information. Uponsuccessful synchronization with the corresponding transmitter unit 102,the primary receiver unit 104 is configured to begin receiving from thetransmitter unit 102 data signals corresponding to the user's detectedanalyte level. More specifically, the primary receiver unit 104 in oneembodiment is configured to perform synchronized time hopping with thecorresponding synchronized transmitter unit 102 via the communicationlink 103 to obtain the user's detected analyte level.

Referring again to FIG. 1, the data processing terminal 105 may includea personal computer, a portable computer such as a laptop or a handhelddevice (e.g., personal digital assistants (PDAs)), and the like, each ofwhich may be configured for data communication with the receiver via awired or a wireless connection. Additionally, the data processingterminal 105 may further be connected to a data network (not shown) forstoring, retrieving and updating data corresponding to the detectedanalyte level of the user.

Within the scope of the present invention, the data processing terminal105 may include an infusion device such as an insulin infusion pump orthe like, which may be configured to administer insulin to patients, andwhich may be configured to communicate with the receiver unit 104 forreceiving, among others, the measured analyte level. Alternatively, thereceiver unit 104 may be configured to integrate an infusion devicetherein so that the receiver unit 104 is configured to administerinsulin therapy to patients, for example, for administering andmodifying basal profiles, as well as for determining appropriate bolusesfor administration based on, among others, the detected analyte levelsreceived from the transmitter unit 102.

Additionally, the transmitter unit 102, the primary receiver unit 104and the data processing terminal 105 may each be configured forbi-directional wireless communication such that each of the transmitterunit 102, the primary receiver unit 104 and the data processing terminal105 may be configured to communicate (that is, transmit data to andreceive data from) with each other via the wireless communication link103. More specifically, the data processing terminal 105 may in oneembodiment be configured to receive data directly from the transmitterunit 102 via the communication link, where the communication link, asdescribed above, may be configured for bi-directional communication.

In this embodiment, the data processing terminal 105 which may includean insulin pump, may be configured to receive the analyte signals fromthe transmitter unit 102, and thus, incorporate the functions of thereceiver 104 including data processing for managing the patient'sinsulin therapy and analyte monitoring. In one embodiment, thecommunication link 103 may include one or more of an RF communicationprotocol, an infrared communication protocol, a Bluetooth enabledcommunication protocol, an 802.11x wireless communication protocol, oran equivalent wireless communication protocol which would allow secure,wireless communication of several units (for example, per HIPAArequirements) while avoiding potential data collision and interference.

FIG. 2 is a block diagram of the transmitter of the data monitoring anddetection system shown in FIG. 1 in accordance with one embodiment ofthe present invention. Referring to the Figure, the transmitter unit 102in one embodiment includes an analog interface 201 configured tocommunicate with the sensor 101 (FIG. 1), a user input 202, and atemperature detection section 203, each of which is operatively coupledto a transmitter processor 204 such as a central processing unit (CPU).As can be seen from FIG. 2, there are provided four contacts, three ofwhich are electrodes—work electrode (W), guard contact (G), referenceelectrode (R), and counter electrode (C), each operatively coupled tothe analog interface 201 of the transmitter unit 102 for connection tothe sensor unit 201 (FIG. 1). In one embodiment, each of the workelectrode (W), guard contact (G), reference electrode (R), and counterelectrode (C) may be made using a conductive material that is eitherprinted or etched, for example, such as carbon which may be printed, ormetal foil (e.g., gold) which may be etched.

Further shown in FIG. 2 are a transmitter serial communication section205 and an RF transmitter 206, each of which is also operatively coupledto the transmitter processor 204. Moreover, a power supply 207 such as abattery is also provided in the transmitter unit 102 to provide thenecessary power for the transmitter unit 102. Additionally, as can beseen from the Figure, clock 208 is provided to, among others, supplyreal time information to the transmitter processor 204.

In one embodiment, a unidirectional input path is established from thesensor 101 (FIG. 1) and/or manufacturing and testing equipment to theanalog interface 201 of the transmitter unit 102, while a unidirectionaloutput is established from the output of the RF transmitter 206 of thetransmitter unit 102 for transmission to the primary receiver unit 104.In this manner, a data path is shown in FIG. 2 between theaforementioned unidirectional input and output via a dedicated link 209from the analog interface 201 to serial communication section 205,thereafter to the processor 204, and then to the RF transmitter 206. Assuch, in one embodiment, via the data path described above, thetransmitter unit 102 is configured to transmit to the primary receiverunit 104 (FIG. 1), via the communication link 103 (FIG. 1), processedand encoded data signals received from the sensor 101 (FIG. 1).Additionally, the unidirectional communication data path between theanalog interface 201 and the RF transmitter 206 discussed above allowsfor the configuration of the transmitter unit 102 for operation uponcompletion of the manufacturing process as well as for directcommunication for diagnostic and testing purposes.

As discussed above, the transmitter processor 204 is configured totransmit control signals to the various sections of the transmitter unit102 during the operation of the transmitter unit 102. In one embodiment,the transmitter processor 204 also includes a memory (not shown) forstoring data such as the identification information for the transmitterunit 102, as well as the data signals received from the sensor 101. Thestored information may be retrieved and processed for transmission tothe primary receiver unit 104 under the control of the transmitterprocessor 204. Furthermore, the power supply 207 may include acommercially available battery.

The transmitter unit 102 is also configured such that the power supplysection 207 is capable of providing power to the transmitter for aminimum of about three months of continuous operation after having beenstored for about eighteen months in a low-power (non-operating) mode. Inone embodiment, this may be achieved by the transmitter processor 204operating in low power modes in the non-operating state, for example,drawing no more than approximately 1 μA of current. Indeed, in oneembodiment, the final step during the manufacturing process of thetransmitter unit 102 may place the transmitter unit 102 in the lowerpower, non-operating state (i.e., post-manufacture sleep mode). In thismanner, the shelf life of the transmitter unit 102 may be significantlyimproved. Moreover, as shown in FIG. 2, while the power supply unit 207is shown as coupled to the processor 204, and as such, the processor 204is configured to provide control of the power supply unit 207, it shouldbe noted that within the scope of the present invention, the powersupply unit 207 is configured to provide the necessary power to each ofthe components of the transmitter unit 102 shown in FIG. 2.

Referring back to FIG. 2, the power supply section 207 of thetransmitter unit 102 in one embodiment may include a rechargeablebattery unit that may be recharged by a separate power supply rechargingunit (for example, provided in the receiver unit 104) so that thetransmitter unit 102 may be powered for a longer period of usage time.Moreover, in one embodiment, the transmitter unit 102 may be configuredwithout a battery in the power supply section 207, in which case thetransmitter unit 102 may be configured to receive power from an externalpower supply source (for example, a battery) as discussed in furtherdetail below.

Referring yet again to FIG. 2, the temperature detection section 203 ofthe transmitter unit 102 is configured to monitor the temperature of theskin near the sensor insertion site. The temperature reading is used toadjust the analyte readings obtained from the analog interface 201. TheRF transmitter 206 of the transmitter unit 102 may be configured foroperation in the frequency band of 315 MHz to 322 MHz, for example, inthe United States. Further, in one embodiment, the RF transmitter 206 isconfigured to modulate the carrier frequency by performing FrequencyShift Keying and Manchester encoding. In one embodiment, the datatransmission rate is 19,200 symbols per second, with a minimumtransmission range for communication with the primary receiver unit 104.

Referring yet again to FIG. 2, not shown is a leak detection circuitcoupled to the guard electrode (G) and the processor 204 in thetransmitter unit 102 of the data monitoring and management system 100.The leak detection circuit in accordance with one embodiment of thepresent invention may be configured to detect leakage current in thesensor 101 to determine whether the measured sensor data are corrupt orwhether the measured data from the sensor 101 is accurate.

Additional detailed description of the continuous analyte monitoringsystem, its various components including the functional descriptions ofthe transmitter are provided in U.S. Pat. No. 6,175,752 issued Jan. 16,2001 entitled “Analyte Monitoring Device and Methods of Use”, and inapplication Ser. No. 10/745,878 filed Dec. 26, 2003 entitled “ContinuousGlucose Monitoring System and Methods of Use”, each assigned to theAssignee of the present application.

FIG. 3 is a block diagram of the receiver/monitor unit of the datamonitoring and management system shown in FIG. 1 in accordance with oneembodiment of the present invention. Referring to FIG. 3, the primaryreceiver unit 104 includes a blood glucose test strip interface 301, anRF receiver 302, an input 303, a temperature detection section 304, anda clock 305, each of which is operatively coupled to a receiverprocessor 307. As can be further seen from the Figure, the primaryreceiver unit 104 also includes a power supply 306 operatively coupledto a power conversion and monitoring section 308. Further, the powerconversion and monitoring section 308 is also coupled to the receiverprocessor 307. Moreover, also shown are a receiver serial communicationsection 309, and an output 310, each operatively coupled to the receiverprocessor 307.

In one embodiment, the test strip interface 301 includes a glucose leveltesting portion to receive a manual insertion of a glucose test strip,and thereby determine and display the glucose level of the test strip onthe output 310 of the primary receiver unit 104. This manual testing ofglucose can be used to calibrate sensor 101. The RF receiver 302 isconfigured to communicate, via the communication link 103 (FIG. 1) withthe RF transmitter 206 of the transmitter unit 102, to receive encodeddata signals from the transmitter unit 102 for, among others, signalmixing, demodulation, and other data processing. The input 303 of theprimary receiver unit 104 is configured to allow the user to enterinformation into the primary receiver unit 104 as needed. In one aspect,the input 303 may include one or more keys of a keypad, atouch-sensitive screen, or a voice-activated input command unit. Thetemperature detection section 304 is configured to provide temperatureinformation of the primary receiver unit 104 to the receiver processor307, while the clock 305 provides, among others, real time informationto the receiver processor 307.

Each of the various components of the primary receiver unit 104 shown inFIG. 3 is powered by the power supply 306 which, in one embodiment,includes a battery. Furthermore, the power conversion and monitoringsection 308 is configured to monitor the power usage by the variouscomponents in the primary receiver unit 104 for effective powermanagement and to alert the user, for example, in the event of powerusage which renders the primary receiver unit 104 in sub-optimaloperating conditions. An example of such sub-optimal operating conditionmay include, for example, operating the vibration output mode (asdiscussed below) for a period of time thus substantially draining thepower supply 306 while the processor 307 (thus, the primary receiverunit 104) is turned on. Moreover, the power conversion and monitoringsection 308 may additionally be configured to include a reverse polarityprotection circuit such as a field effect transistor (FET) configured asa battery activated switch.

The serial communication section 309 in the primary receiver unit 104 isconfigured to provide a bi-directional communication path from thetesting and/or manufacturing equipment for, among others,initialization, testing, and configuration of the primary receiver unit104. Serial communication section 309 can also be used to upload data toa computer, such as time-stamped blood glucose data. The communicationlink with an external device (not shown) can be made, for example, bycable, infrared (IR) or RF link. The output 310 of the primary receiverunit 104 is configured to provide, among others, a graphical userinterface (GUI) such as a liquid crystal display (LCD) for displayinginformation. Additionally, the output 310 may also include an integratedspeaker for outputting audible signals as well as to provide vibrationoutput as commonly found in handheld electronic devices, such as mobiletelephones presently available. In a further embodiment, the primaryreceiver unit 104 also includes an electro-luminescent lamp configuredto provide backlighting to the output 310 for output visual display indark ambient surroundings.

Referring back to FIG. 3, the primary receiver unit 104 in oneembodiment may also include a storage section such as a programmable,non-volatile memory device as part of the processor 307, or providedseparately in the primary receiver unit 104, operatively coupled to theprocessor 307. The processor 307 is further configured to performManchester decoding as well as error detection and correction upon theencoded data signals received from the transmitter unit 102 via thecommunication link 103.

FIG. 4 is a functional diagram of the overall signal processing fornoise filtering and signal dropout compensation, while FIG. 5 shows aflowchart illustrating the overall signal processing for noise filteringand signal dropout compensation in accordance with one embodiment of thepresent invention. Referring to the Figures, in one embodiment, signalsmeasured are received from, for example, the analyte sensor 101 (FIG. 1)and are provided to the state observer 410 which in one embodiment maybe configured to provide prior or past noise filtered estimate to aprocess input estimator 420.

In one embodiment, the process input estimator 420 may be configured togenerate a process input estimate based on the prior or past noisefiltered estimate of the received or measured signal (510), which isthen provided to the state observer 410. In one aspect, and as describedin further detail below in conjunction with FIG. 6, the process inputestimate at a predetermined time t may be based on past noise filteredestimate of the signal.

Thereafter, in one embodiment, the state observer 410 may be configuredto generate a noise filtered estimate of the measured or received signalbased on the current measured or received signal and the process inputestimate (520) received from the process input estimator 420. In oneembodiment and as described in further detail below in conjunction withFIG. 7, using the real time process input and sensor measurementsignals, a noise filtered estimate of the signal at the latest time tmay be determined.

In one aspect, this routine of generating the process input estimatebased on the past noise filtered estimate of the received or measuredsignal, and generating the noise filtered estimate of the signal basedon the current received or measured signal and the current determined orgenerated process input estimate may be repeated for each measurementsignal received, for example, from the analyte sensor 101 (FIG. 1). Inthis manner, in one aspect, the noise filtered signals corresponding tothe measured or received sensor signals may be determined.

Referring back to FIGS. 4 and 5, in one embodiment, with the noisefiltered estimate, the presence of signal dropouts are detected basedon, for example, the current and past noise filtered estimate of thereceived or measured signal (530). More specifically, in one embodiment,a dropout detector 430 may be configured to detect signal dropouts, andthereafter, detection of signal dropouts are provided to dropoutcompensator 440. In one aspect, the dropout detector 430 may beconfigured to generate a signal or notification associated with thedetection of a signal dropout (as shown in FIG. 4). That is, in oneembodiment and as described in further detail below in conjunction withFIG. 8, the dropout detector 430 may be configured to detect or estimatethe presence or absence of signal dropouts at the predetermined time.

In one embodiment, the dropout compensator 440 may be configured togenerate an estimate of the noise filtered, dropout compensated signal(540) when the signal dropout is detected (for example, by the dropoutdetector 430), by subtracting the estimate of the current dropout signalsource from the present noise filtered estimate of the signal. In thismanner, and as described in further detail below in conjunction withFIGS. 9-10, in one embodiment of the present invention, the noisefiltered signal dropout mitigated or compensated signal may be generatedto improve accuracy of the measured or received signal from, forexample, the analyte sensor 101 (FIG. 1).

FIG. 6 is a flowchart illustrating the process input estimation inaccordance with one embodiment of the present invention. Referring toFIG. 6, a mean component of the process input estimate u_(m)(t) based onpast noise filtered estimate of the signal is generated (610). Forexample, in one embodiment, a series of five past noise-filteredestimate of the signal, x_(i)(t−5), x_(i)(t−4), x_(i)(t−3), x_(i)(t−2),x_(i)(t−1), the mean component of the process input estimate at time t,u_(m)(t) may be determined by taking the unweighted average of thesesignals as shown by the following relationship:

$\begin{matrix}{{u_{m}(t)} = \frac{{x_{i}\left( {t - 5} \right)} + {x_{i}\left( {t - 4} \right)} + {x_{i}\left( {t - 3} \right)} + {x_{i}\left( {t - 2} \right)} + {x_{i}\left( {t - 1} \right)}}{5}} & (1)\end{matrix}$

Alternatively, the mean component of the process input estimate at timet may be determined by taking the weighted average of these signals asshown by the following relationship:

$\begin{matrix}{{u_{m}(t)} = \frac{\begin{matrix}{{a_{5}{x_{i}\left( {t - 5} \right)}} + {a_{4}x_{i}\left( {t - 4} \right)} +} \\{{a_{3}{x_{i}\left( {t - 3} \right)}} + {a_{2}{x_{i}\left( {t - 2} \right)}} + {a_{1}{x_{i}\left( {t - 1} \right)}}}\end{matrix}}{a_{5} + a_{4} + a_{3} + a_{2} + a_{1}}} & (2)\end{matrix}$

where the determination of the constants a₁, a₂, a₃, a₄, a₅, may beobtained based on empirical or analytical analysis of the analytemonitoring system.

In yet another embodiment, the mean component of the process inputestimate at time t based on recent past data may be determined usingfiltering techniques, such as, but not limited to FIR filters.

Referring to FIG. 6, with the mean component of the process inputestimate u_(m)(t) based on past noise filtered estimate of the signaldetermined, the difference component of the process input estimate atany time t, u_(d)(t), may be generated (620) by, for example, taking anaveraged difference of a series of noise-filtered estimate of the signalfrom the recent past. In one aspect, an unweighted average of the lastthree past differences may be used in the following manner:

$\begin{matrix}{{u_{d}(t)} = \frac{\begin{matrix}{\left( {{x_{i}\left( {t - 4} \right)} - {x_{i}\left( {t - 3} \right)}} \right) + \left( {{x_{i}\left( {t - 3} \right)} - {x_{i}\left( {t - 2} \right)}} \right) +} \\\left( {{x_{i}\left( {t - 2} \right)} - {x_{i}\left( {t - 1} \right)}} \right)\end{matrix}}{3}} & (3)\end{matrix}$

Within the scope of the present invention, other approaches such as theuse of FIR filter to determine the proper number of recent past valuesof x_(i) as well as the weighting of each difference may be used.

Referring again to FIG. 6, after determining the difference component ofthe process input estimate at any time t, u_(d)(t), the difference gainat any time t, K_(d)(t), is determined (630), for example, by using pastnoise-filtered estimate of the signal, x_(i), and/or the derived signalsfrom x_(i). For example, in one embodiment, a band-limited rate X_(i)_(—) _(bandRate) and a band-limited acceleration x_(i) _(—) _(bandAcc),may be determined at any time t, based solely on recent past values ofx_(i). Using the knowledge of how the amount of u_(d) would contributeto the total process input u at any time t relates to these twovariables X_(i) _(—) _(bandRate) and X_(i) _(—) _(bandAcc), a functionalrelationship may be determined to ascertain the value of the differencegain K_(d) at any time t.

Alternatively, a lookup table can be constructed that determines thevalue of the difference gain K_(d) given the values of X_(i) _(—)_(bandRate) and X_(i) _(—) _(bandAcc) as shown below:

$\begin{matrix}{K_{d} = \left\{ \begin{matrix}2 & {{{{if}\mspace{14mu} \left( {X_{i\_ bandRate} > 0} \right)}\&}\mspace{14mu} \left( {x_{i\_ bandAcc} > 0} \right)} \\1 & {{{{if}\mspace{14mu} \left( {x_{i\_ bandRate} > 0} \right)}\&}\mspace{14mu} \left( {x_{i\_ bandAcc} \leqq 0} \right)} \\1 & {{{{if}\mspace{14mu} \left( {x_{i\_ bandRate} \leqq 0} \right)}\&}\mspace{14mu} \left( {x_{i\_ bandAcc} \leqq 0} \right)} \\0.5 & {{{{if}\mspace{14mu} \left( {x_{i\_ bandRate} \leqq 0} \right)}\&}\mspace{14mu} \left( {x_{i\_ bandAcc} > 0} \right)}\end{matrix} \right.} & (4)\end{matrix}$

In one aspect, the difference gain K_(d) may be used to scale thecontribution of the difference component of the process input estimateu_(d) in the value of the process input estimate at a given time. Forexample, a relatively larger value of the difference gain K_(d) mayindicate a larger contribution of the difference component of theprocess input estimate u_(d) in the value of the process input estimateat the particular time, and so on. In this manner, in one aspect, thelookup table may show the relationship between factors such as theband-limited rate X_(i) _(—) _(bandRate) and the band-limitedacceleration x_(i) _(—) _(bandAcc) upon how much the differencecomponent of the process input estimate u_(d) should contribute to theprocess input estimate value.

Referring again to FIG. 6, with the mean component of the process inputestimate u_(m)(t), the difference component of the process inputestimate at any time t, u_(d)(t), and the difference gain at any time t,K_(d)(t), the scaled difference component u_(ds)(t) of the process inputestimate may be determined (640) by multiplying the difference componentof the process input estimate at any time t, u_(d)(t) by the differencegain at any time t, K_(d)(t). Thereafter, the scaled differencecomponent u_(ds)(t) of the process input estimate may be added to themean component of the process input estimate u_(m)(t) to determine thecurrent process input estimate value u(t) (650).

FIG. 7 is a flowchart illustrating the noise filtered estimation.Referring to FIG. 7, with an estimate of process input signal at anytime t, u(t), and based on the measured signals from the analyte sensorz(t), in addition to past estimates of the noise-filtered signalx_(i)(t−1), x_(i)(t−2), . . . , the state observer 410 (FIG. 4) may beconfigured to determine the estimate of noise-filtered signal at anytime t, x_(i)(t). In one aspect, the state observer 410 (FIG. 4) may beconfigured to reduce the contribution of noise without introducingexcessive undesirable distortion based on the estimate of process inputsignal at any time t, u(t), and the measured signals from the sensorz(t).

FIG. 8 is a flowchart illustrating signal dropout detection inaccordance with one embodiment of the present invention. Referring toFIG. 8, a present “fast rate” estimate x_(df)(t) is determined based onpresent and past noise-filtered estimate of the signal (810). Forexample, a difference signal x_(d)(t) may be determined based on thefollowing expression:

x _(d)(t)=x _(i)(t)−x _(i)(t−1)  (5)

Thereafter, a fast rate may be extracted from the difference signalx_(d)(t) by performing high pass filtering on the difference signalx_(d)(t). In one embodiment, a discrete-time realization of a firstorder high pass filter function may be used to determine the present“fast rate” estimate x_(df)(t):

x _(df)(t)=a _(hpfD) x _(df)(t−1)+x _(d)(t)−x _(d)(t−1)  (6)

where the value of a_(hpfD), or the structure of the high pass filtermay be determined in accordance with the suitable design configurations,for example, a value between zero and one.

Referring back to FIG. 8, after determining the “fast rate” estimatex_(df)(t), a present “slow rate” estimate x_(ds)(t) is determined basedon present and past noise-filtered estimate of the signal (820). Forexample, in one embodiment, the slow rate estimate x_(ds)(t) may bedetermined by passing the simple difference through a low-pass filter,or alternatively, by taking the difference between the simple differenceand the fast difference signals as shown, for example, by the followingexpression:

x _(ds)(t)=x _(d)(t)−x _(df)(t)  (7)

After determining the slow rate estimate x_(ds)(t), it is determinedwhether there is a beginning of a large negative spike in the fast rateestimate x_(df)(t) (830). That is, referring to FIG. 8, the start of asignal dropout state is determined which is correlated to a spike in thefast difference. The fast difference does not generate a spike largerthan a predetermined value in response to signals generated in theabsence of dropouts. For example, adjusted to the units of glucoseconcentration, this may correspond to a fast rate in excess of −3 mg/(dLmin). Although a rate of −3 mg/(dL min) or faster may be ascertained,when band pass filtered, the fast rate estimate x_(df)(t) determinedabove does not occur in this range unless a signal dropout occurs.

Referring back to FIG. 8, if the beginning of a large negative spike inthe fast rate estimate x_(df)(t) is detected, then the elapsed timeperiod from the initial occurrence of the large negative spike ismonitored (840), for example, by triggering a timer or a counter so asto monitor the elapsed time since the most recent signal dropoutoccurrence predicted estimate. In this manner, a safety check mechanismmay be provided to determine situations where a signal dropout that wasanticipated to have started has lasted in an undesirably long period ofdropout time period. That is, as the signal dropouts are generallyintermittent in nature, it is expected that the dropout does not lastbeyond the order of one hour, for example, and more commonly, in theorder of five to 30 minutes.

Thereafter, it is determined whether a predetermined allowable timeperiod has elapsed (850). As shown in FIG. 8, if it is determined theallowable time period has not elapsed, then the beginning or onset ofthe signal dropout is estimated. On the other hand, if the predeterminedallowable time period has elapsed, then the end of the signal dropout isestimated. Referring again to FIG. 8, when the beginning of a largenegative spike in the fast rate estimate x_(df)(t) is not detected, itis determined whether an end of a large positive spike (for example, inthe order of +3 mg/(dL min)) in the fast rate estimate x_(df)(t) isdetected (860). If the end of the large positive spike in the fast rateestimate x_(df)(t) is detected, then the end of the signal dropout isestimated. On the other hand, if the end of the large positive spike inthe fast rate estimate x_(df)(t) is not detected, then no signal dropoutis estimated.

That is, a signal dropout is generally correlated to a large positivespike in the fast difference. Thus, in this case, the tail of the largepositive spike is monitored and detected as the end of the signaldropout. In one embodiment, this maximizes the likelihood of detectingmost of the instances within a signal dropout.

In this manner, in one embodiment of the present invention, the presenceof signal dropout may be monitored and detected based on, for example,present and past noise filtered estimate of the signals.

FIG. 9 is a flowchart illustrating an overall signal dropoutcompensation in accordance with one embodiment of the present invention.Referring to FIG. 9, a momentum-based estimate is determined based onthe present slow difference and previous momentum-based estimate (910).That is, with the present and past noise filtered estimate of thesignal, the present and past slow and fast rate estimates determined asdescribed above, and with the signal dropout detection estimationdetermined above, the momentum-based estimate is determined based on thepresent slow difference and previous momentum-based estimate. That is,in one embodiment, a momentum-based estimate may factor in a signalwithout dropouts as being likely to project (e.g., extrapolate) based onits past signal and its prior trend.

Referring back to FIG. 9, after determining the momentum based estimateusing the present slow difference and prior momentum-based estimate, anaveraged value of the present or current momentum-based estimate and thepresent noise filtered estimate is determined (920). Thereafter, aninertial gain based on the present and past slow rate estimate isdetermined (930), and which may be configured to scale the contributionof the momentum-based estimate determined using the present slowdifferent and the previous momentum based estimate above in the finaldropout compensated gain. Referring again to FIG. 9, after determiningthe inertial gain, a tracking gain is determined based on the inertialgain (940). In one embodiment, the determined tracking gain may beconfigured to scale the impact of the determined average value of thepresent momentum-based estimate and the present noise-filtered estimate,in the determination of the final dropout compensated signal (950) asdiscussed below.

Referring to FIG. 9, after determining the tracking gain, the dropoutcompensated signal is determined (950). In one embodiment, thedropout-compensated signal equals the noise-filtered estimate of thesignal x_(i), when no dropout is estimated. Otherwise, the dropoutcompensated signal may be a weighted average of the momentum-basedestimate (x_(momentum)) as discussed above and the averaged momentum andnoise-filtered estimate (x_(average)) also discussed above. In oneaspect, the weighing factors for the weighted average of themomentum-based estimate (x_(momentum)) and the averaged momentum andnoise-filtered estimate (x_(average)) may be the inertial gainK_(inertial) and tracking gain K_(tracking), respectively. For example,the dropout compensated signal at any time t, x′_(dci)(t) in oneembodiment may be determined in accordance with the followingrelationship:

x′ _(dci)(t)=(K _(inertial)(t)x _(momentum)(t)+(K _(tracking)(t)x_(average)(t))  (8)

In a further embodiment, the determination of the dropout compensatedsignal at any time t, x′_(dci)(t) may be refined to ensure a smoothtransition depending upon the underlying conditions, as described infurther detail below in conjunction with FIG. 10.

Referring back to FIG. 9, after determining the dropout compensatedsignal, the dropout compensated signal may be clipped to be within apredetermined range (960), for example, such that the dropoutcompensated signal is not less than the noise-filtered signal, andfurther, that it is not greater than a specified safety ratio times thenoise-filtered signal.

In certain cases, the resulting value of the dropout compensated signalx′_(dci)(t) may fall below the noise-filtered estimate x_(i)(t). Sinceby definition, a dropout is a phenomena that can only reduce the truevalue of a signal, the relationship (8) above for determining thedropout compensated signal may be modified by ensuring that its valuenever goes below x_(i)(t) at any given time, and as shown by thefollowing expression:

$\begin{matrix}{{x_{dci}(t)} = \left\{ \begin{matrix}{x_{dci}^{\prime}(t)} & {{{for}\mspace{14mu} {x_{dci}^{\prime}(t)}} \geqq {x_{i}(t)}} \\{x_{i}(t)} & {{{for}\mspace{14mu} {x_{dci}^{\prime}(t)}} < {x_{i}(t)}}\end{matrix} \right.} & (9)\end{matrix}$

FIG. 10 is flowchart illustrating a detailed signal dropout compensationdetermination of FIG. 9 in accordance with one embodiment of the presentinvention. Referring to FIG. 10, for example, in determining thedrop-compensated signal, it is first determined whether signal dropoutis detected. If signal dropout is not detected, then it is determinedwhether a preset time period has elapsed since the end of the lastdropout occurrence. If it is determined that a preset time period haselapsed, then the dropout compensated signal may be based upon thepresent noise filtered signal. In one aspect, the preset time period maybe a predetermined time period that may be considered a long period oftime. On the other hand, if it is determined that the preset time periodhas not elapsed (that is, the end of the occurrence of a signal dropouthas recently occurred), then the dropout compensated signal may be basedupon a smooth transition using the previous dropout compensated signaland the present noise filtered signal.

Indeed, referring to FIG. 10, it can be seen that depending upon thedetermination of the timing of the signal dropout occurrence, inparticular embodiments, the dropout compensated signal may be determinedbased on one or more factors as shown in the Figure and also describedabove.

Referring again to the Figures, in particular embodiments, theprocessings associated with the noise filtering, signal dropoutdetection estimation and compensation may be performed by one or moreprocessing units of the one or more receiver unit (104, 106) thetransmitter unit 102 or the data processing terminal/infusion section105. In addition, the one or more of the transmitter unit 102, theprimary receiver unit 104, secondary receiver unit 106, or the dataprocessing terminal/infusion section 105 may also incorporate a bloodglucose meter functionality, such that, the housing of the respectiveone or more of the transmitter unit 102, the primary receiver unit 104,secondary receiver unit 106, or the data processing terminal/infusionsection 105 may include a test strip port configured to receive a bloodsample for determining one or more blood glucose levels of the patient.

In a further embodiment, the one or more of the transmitter unit 102,the primary receiver unit 104, secondary receiver unit 106, or the dataprocessing terminal/infusion section 105 may be configured to receivethe blood glucose value wirelessly over a communication link from, forexample, a glucose meter. In still a further embodiment, the user orpatient manipulating or using the analyte monitoring system 100 (FIG. 1)may manually input the blood glucose value using, for example, a userinterface (for example, a keyboard, keypad, and the like) incorporatedin the one or more of the transmitter unit 102, the primary receiverunit 104, secondary receiver unit 106, or the data processingterminal/infusion section 105.

A method in one embodiment includes monitoring a data stream, generatinga noise-filtered signal associated with the data stream, detecting apresence of a signal dropout based on the noise filtered signal, andestimating a noise filtered dropout compensated signal based on thenoise filtered signal and the determination of the presence of thesignal dropout.

In one aspect, generating the noise filtered signal may includegenerating one or more frequency-shaped signals based on the monitoreddata stream, and further, which may include high pass filtering themonitored data stream.

Also, generating the noise filtered signal in another aspect may bebased on one or more previous noise filtered signals.

The method in a further embodiment may include outputting the noisefiltered signal. The method in still another aspect may includeoutputting the noise filtered dropout compensated signal.

The method may also include generating a signal associated withdetecting the presence of a signal dropout.

Moreover, the data stream in one embodiment may be associated with amonitored analyte levels of a patient.

An apparatus in another embodiment includes one or more processors, anda memory for storing instructions which, when executed by the one ormore processors, causes the one or more processors to monitor a datastream, generate a noise-filtered signal associated with the datastream, detect a presence of a signal dropout based on the noisefiltered signal, and estimate a noise filtered dropout compensatedsignal based on the noise filtered signal and the determination of thepresence of the signal dropout.

The memory may be further configured for storing instructions which,when executed by the one or more processors, causes the one or moreprocessors to generate one or more frequency-shaped signals based on themonitored data stream.

In another aspect, the memory may be further configured for storinginstructions which, when executed by the one or more processors, causesthe one or more processors to generate the one or more frequency shapedsignals by high pass filtering the monitored data stream.

In still another aspect, the memory may be further configured forstoring instructions which, when executed by the one or more processors,causes the one or more processors to generate the noise filtered signalbased on one or more previous noise filtered signals.

Moreover, the memory may be further configured for storing instructionswhich, when executed by the one or more processors, causes the one ormore processors to output the noise filtered signal.

In yet another embodiment, the memory may be further configured forstoring instructions which, when executed by the one or more processors,causes the one or more processors to output the noise filtered dropoutcompensated signal.

Additionally, the memory may be further configured for storinginstructions which, when executed by the one or more processors, causesthe one or more processors to generate a signal associated withdetecting the presence of a signal dropout.

A system in accordance with still another embodiment may include ananalyte sensor configured to monitor an analyte of a patient, a dataprocessing section operatively coupled to the analyte sensor, the dataprocessing section further including one or more processors, and amemory for storing instructions which, when executed by the one or moreprocessors, causes the one or more processors to monitor a data stream,generate a noise-filtered signal associated with the data stream, detecta presence of a signal dropout based on the noise filtered signal, andestimate a noise filtered dropout compensated signal based on the noisefiltered signal and the determination of the presence of the signaldropout.

The data processing section may include a data transmission unitoperatively coupled to one or more processors configured to transmit thedata stream. In another aspect, the data processing section may includea data receiving unit operatively coupled to the one or more processorsand configured to receive the data stream.

The analyte sensor may include a glucose sensor.

Moreover, the memory may be further configured for storing instructionswhich, when executed by the one or more processors, causes the one ormore processors to store one or more of the data stream, the noisefiltered signal, or the noise filtered dropout compensated signal.

The various processes described above including the processes performedby the receiver unit 104/106 or transmitter unit 102 in the softwareapplication execution environment in the analyte monitoring system 100including the processes and routines described in conjunction with FIGS.5-10, may be embodied as computer programs developed using an objectoriented language that allows the modeling of complex systems withmodular objects to create abstractions that are representative of realworld, physical objects and their interrelationships. The softwarerequired to carry out the inventive process, which may be stored in thememory or storage unit of the receiver unit 104/106 or transmitter unit102 may be developed by a person of ordinary skill in the art and mayinclude one or more computer program products.

Various other modifications and alterations in the structure and methodof operation of this invention will be apparent to those skilled in theart without departing from the scope and spirit of the invention.Although the invention has been described in connection with specificpreferred embodiments, it should be understood that the invention asclaimed should not be unduly limited to such specific embodiments. It isintended that the following claims define the scope of the presentinvention and that structures and methods within the scope of theseclaims and their equivalents be covered thereby.

1. A method, comprising: generating a noise filtered signal associatedwith a monitored analyte related data stream based on one or more priorfiltered signals; detecting a signal dropout in the noise filteredsignal; and estimating, using one or more processors, a dropoutcompensated signal based on the noise filtered signal and the detectionof the signal dropout.
 2. The method of claim 1 wherein the one or moreprior filtered signals includes one or more prior noise filtered signalsassociated with the monitored analyte related data stream.
 3. The methodof claim 1 further comprising generating a signal associated with thedetected signal dropout, wherein estimating the dropout compensatedsignal includes determining a variation between the signal associatedwith the detected signal dropout and the generated noise filteredsignal.
 4. The method of claim 1 wherein estimating the dropoutcompensated signal includes subtracting the signal associated with thedetected signal dropout and the generated noise filtered signal.
 5. Themethod of claim 1 wherein generating the noise filtered signal includesapplying a filter to the monitored analyte related data stream.
 6. Themethod of claim 1 wherein generating the noise filtered signal includesapplying a weighted average function to the monitored analyte relateddata stream.
 7. The method of claim 1 further including outputting thedropout compensated signal, and wherein outputting the dropoutcompensated signal includes providing an indication associated with thenoise filtered signal.
 8. The method of claim 1 including transmittingone or more of the monitored analyte related data stream, the noisefiltered signal, the detected signal dropout, or the dropout compensatedsignal.
 9. The method of claim 8 wherein said transmitting includeswirelessly transmitting the one or more of the monitored analyte relateddata stream, the noise filtered signal, the detected signal dropout, orthe dropout compensated signal.
 10. The method of claim 8 includingtransmitting the one or more of the monitored analyte related datastream, the noise filtered signal, the detected signal dropout, or thedropout compensated signal to a remote location.
 11. An apparatus,comprising: one or more processors; and a memory storing instructionswhich, when executed by the one or more processors, causes the one ormore processors to generate a noise filtered signal associated with amonitored analyte related data stream based on one or more priorfiltered signals, to detect a signal dropout in the noise filteredsignal, and to estimate a dropout compensated signal based on the noisefiltered signal and the detection of the signal dropout.
 12. Theapparatus of claim 11 wherein the one or more prior filtered signalsincludes one or more prior noise filtered signals associated with themonitored analyte related data stream.
 13. The apparatus of claim 11wherein the memory stores instructions which, when executed by the oneor more processors, causes the one or more processors to generate asignal associated with the detected signal dropout and to determine avariation between the signal associated with the detected signal dropoutand the generated noise filtered signal.
 14. The apparatus of claim 11wherein the memory stores instructions which, when executed by the oneor more processors, causes the one or more processors to subtract thesignal associated with the detected signal dropout and the generatednoise filtered signal.
 15. The apparatus of claim 11 wherein the memorystores instructions which, when executed by the one or more processors,causes the one or more processors to apply a filter to the monitoredanalyte related data stream.
 16. The apparatus of claim 11 wherein thememory stores instructions which, when executed by the one or moreprocessors, causes the one or more processors to apply a weightedaverage function to the monitored analyte related data stream.
 17. Theapparatus of claim 11 wherein the memory stores instructions which, whenexecuted by the one or more processors, causes the one or moreprocessors to output the dropout compensated signal.
 18. The apparatusof claim 17 wherein the memory stores instructions which, when executedby the one or more processors, causes the one or more processors toprovide an indication associated with the noise filtered signal.
 19. Theapparatus of claim 11 wherein the memory stores instructions which, whenexecuted by the one or more processors, causes the one or moreprocessors to transmit one or more of the monitored analyte related datastream, the noise filtered signal, the detected signal dropout, or thedropout compensated signal.